Institutional Forecasting: The Performance of Thin Virtual Stock Markets
AbstractWe study the performance of Virtual Stock Markets (VSMs) in an institutional forecasting environment. We compare VSMs to the Combined Judgmental Forecast (CJF) and the Key Informant (KI) approach. We find that VSMs can be effectively applied in an environment with a small number of knowledgeable informants, i.e., in thin markets. Our results show that none of the three approaches differ in forecasting accuracy in a low knowledge-heterogeneity environment. However, where there is high knowledge-heterogeneity, the VSM approach outperforms the CJF approach, which in turn outperforms the KI approach. Hence, our results provide useful insight into when each of the three approaches might be most effectively applied.
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Bibliographic InfoPaper provided by Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam in its series ERIM Report Series Research in Management with number ERS-2006-028-MKT.
Date of creation: 23 Jun 2006
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Electronic Markets; Forecasting; Information Markets; Virtual Stock Markets;
Find related papers by JEL classification:
- C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- M - Business Administration and Business Economics; Marketing; Accounting
- M31 - Business Administration and Business Economics; Marketing; Accounting - - Marketing and Advertising - - - Marketing
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- Justin Wolfers & Eric Zitzewitz, 2004.
Journal of Economic Perspectives,
American Economic Association, vol. 18(2), pages 107-126, Spring.
- Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," Discussion Papers 03-025, Stanford Institute for Economic Policy Research.
- Wolfers, Justin & Zitzewitz, Eric, 2004. "Prediction Markets," Working paper 259, Regulation2point0.
- Wolfers, Justin & Zitzewitz, Eric, 2004. "Prediction Markets," Research Papers 1854, Stanford University, Graduate School of Business.
- Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," NBER Working Papers 10504, National Bureau of Economic Research, Inc.
- Garthwaite, Paul H. & Kadane, Joseph B. & O'Hagan, Anthony, 2005. "Statistical Methods for Eliciting Probability Distributions," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 680-701, June.
- Sanmay Das, 2005. "A learning market-maker in the Glosten-Milgrom model," Quantitative Finance, Taylor & Francis Journals, vol. 5(2), pages 169-180.
- Anderson, Lisa R & Holt, Charles A, 1997. "Information Cascades in the Laboratory," American Economic Review, American Economic Association, vol. 87(5), pages 847-62, December.
- Forsythe, Robert & Lundholm, Russell, 1990. "Information Aggregation in an Experimental Market," Econometrica, Econometric Society, vol. 58(2), pages 309-47, March.
- Kenneth Oliven & Thomas A. Rietz, 2004. "Suckers Are Born but Markets Are Made: Individual Rationality, Arbitrage, and Market Efficiency on an Electronic Futures Market," Management Science, INFORMS, vol. 50(3), pages 336-351, March.
- Grossman, Sanford J & Stiglitz, Joseph E, 1980.
"On the Impossibility of Informationally Efficient Markets,"
American Economic Review,
American Economic Association, vol. 70(3), pages 393-408, June.
- Sanford J Grossman & Joseph E Stiglitz, 1997. "On the Impossibility of Informationally Efficient Markets," Levine's Working Paper Archive 1908, David K. Levine.
- repec:reg:rpubli:259 is not listed on IDEAS
- Plott, Charles R. & Sunder, Shyam., .
"Efficiency of Experimental Security Markets with Insider Information: An Application of Rational Expectations Models,"
331, California Institute of Technology, Division of the Humanities and Social Sciences.
- Plott, Charles R & Sunder, Shyam, 1982. "Efficiency of Experimental Security Markets with Insider Information: An Application of Rational-Expectations Models," Journal of Political Economy, University of Chicago Press, vol. 90(4), pages 663-98, August.
- Stracca, Livio, 2004. "Behavioral finance and asset prices: Where do we stand?," Journal of Economic Psychology, Elsevier, vol. 25(3), pages 373-405, June.
- Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
- Sunder, Shyam, 1992.
"Market for Information: Experimental Evidence,"
Econometric Society, vol. 60(3), pages 667-95, May.
- Kay-Yut Chen & Leslie R. Fine & Bernardo A. Huberman, 2004. "Eliminating Public Knowledge Biases in Information-Aggregation Mechanisms," Management Science, INFORMS, vol. 50(7), pages 983-994, July.
- Martin Spann & Bernd Skiera, 2003. "Internet-Based Virtual Stock Markets for Business Forecasting," Management Science, INFORMS, vol. 49(10), pages 1310-1326, October.
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